Description
Responsibilities: Develop AI and Machine Learning models for energy price, consumption, and production forecasting. Build algorithms that support and optimize energy trading decisions. Automate the collection, processing, and integration of energy market and weather data.
Develop and maintain data pipelines for AI models. Deploy, monitor, and improve AI models in production environments. Create dashboards and reports to support traders' decision-making (Power BI).
Collaborate closely with the Trading team to develop AI-driven solutions. Ensure AI models are compliant with industry regulations and properly documented for audit purposes. Technical skills: Advanced knowledge of Machine Learning (supervised/unsupervised learning, time series modeling) Experience with Deep Learning models (LSTM, Transformer, CNN) Experience in energy forecasting (prices, production, imbalances) Ability to develop AI algorithms for bidding, arbitrage and trading strategies Knowledge of risk analysis, simulations and cost estimation Experience with MLOps tools (MLflow, Kubeflow, Azure ML) Strong Data Engineering skills (ETL, Airflow, Spark, dbt, SQL) Advanced Python skills (pandas, scikit-learn, PyTorch) and Git Experience with data visualization tools (Power BI) Knowledge of REST APIs and system integrations (OPCOM/BRM APIs) Experience with cloud platforms (Azure MS Fabric) Knowledge of AI model explainability techniques (SHAP, LIME) Analytical & business skills: Understanding of energy trading markets (DAM, IDM, BRM, SIDC) Ability to align AI solutions with business and commercial objectives Soft skills: Ability to explain complex AI concepts to non-technical stakeholders Strong collaboration skills with technical and business teams Strategic thinking and problem-solving mindset Adaptability to market and regulatory changes Professional ethics and focus on transparent AI usage
Employer contacts (email/phone/telegram) are hidden from the public preview —
send your CV, and we will connect you directly.